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Welcome to the February 2, 2022, edition of ACM TechNews, providing timely information for IT professionals three times a week.

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An antigenic map shows the major variants of COVID-19 that have buffeted the world so far. Algorithm That Mapped Omicron Shows Path Forward
IEEE Spectrum
Emily Waltz
February 1, 2022


The antigenic cartography algorithm, which can two-dimensionally map laboratory data on viral strains, has helped scientists keep up with genetic variants. Derek Smith at the U.K.'s University of Cambridge and Ron Fouchier at Erasmus Medical Center in the Netherlands developed the algorithm, which interprets and visualizes data as a color-coded map that clusters antigenically similar viruses closer together. Over a dozen labs convened by the U.S. National Institutes of Health are applying antigenic cartography to COVID variants. Recent research yielded an antigenic map plotting omicron's relationship to prior variants. Antigenic mapping plays a central role in forecasting future variants and developing appropriate vaccines.

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Team Creates 3D Objects That Change Their Appearance From Different Viewpoints
MIT Materials Research Laboratory
Elizabeth A. Thomson
January 26, 2022


A team of researchers at the Massachusetts Institute of Technology has developed a system for producing three-dimensional (3D) objects whose appearance changes when viewed from different angles. Lenticular lenses are printed across the object, each covering a pattern of tiny colored image spots. Multiple lenticular lenses together "form a lenticular display and collectively show an image that varies dependent on viewpoint," according to the researchers. An editing tool is used to take the desired 3D object and the images a designer wants to morph from one into another as input; it then calculates lens placement and color patterns across the object's surface that will induce the desired effect. The designer can preview the object before directing a 3D printer to manufacture it.

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Art teacher Sarah Hager works at a computer in her classroom at Cleveland Middle School. Hackers Prey on Public Schools, Adding Stress Amid Pandemic
Associated Press
Cedar Attanasio
January 31, 2022


Cyberattacks are a growing threat to U.S. public schools, as evidenced by an attack on a New Mexico middle school that canceled classes for two days. The ransomware attack blocked the district's student database and locked teachers out of class rosters and grades. These attacks come as schools are increasingly dependent on technology and more educators are sick or in quarantine amid the pandemic. The Virginia-based non-profit K12 Security Information Exchange has tracked more than 1,200 cybersecurity incidents at public school districts nationwide since 2016. These include 209 ransomware attacks, 53 "denial of service" attacks, 156 "Zoombombings," and more than 110 phishing attacks. Brett Callow of anti-virus software maker Emsisoft said that last year, ransomware gangs increasingly targeted smaller school districts, possibly because larger districts boosted their cybersecurity spending.

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Sifting through footage to identify wounded animals is made easier by AI. AI Can Spot Wounded Wild Animals, Poachers in Camera Trap Footage
New Scientist
Matthew Sparkes
January 25, 2022


An artificial intelligence (AI) model developed by researchers at the U.K.'s Liverpool John Moores University can identify animals, any wounds they might have, and track their movements in the wild based on video footage from camera traps. The new model can help minimize the amount of time conservationists spend reviewing such video. The AI model has identified 44 different species in motion-activated camera footage, overhead images from drones, and audio. The researchers applied an algorithm used by the U.K.'s National Health Service to detect bed sores in older patients to identify wounds on animals in the video footage, achieving similar accuracy rates. The models were trained on 200,000 images of 44 species of animals and humans. The researchers created a software model specific to each continent, each demonstrating an accuracy rate of up to 95%.

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Researchers Develop Automated Approach to Extract Security Policies From Software
UTSA Today
Valerie Bustamante Johnson
January 31, 2022


University of Texas at San Antonio (UTSA) researchers have devised a machine learning (ML) model that could train software to extract security policies automatically. The model executes predictions using access control classification, named entity recognition, and access type classification. Access control classification helps the software determine if user stories feature access control information; named entity recognition identifies actors and data objects within the story; and access type classification learns the relationship between the two. UTSA's Ram Krishnan said the team used a dataset of 1,600 user stories to create a learning model based on the transformers ML technique. "We were able to extract security policies with good accuracy and visualize the results to help stakeholders better refine user stories and maintain an overview of the system's access control," he said.

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An image of the holographic self-checkout machine in use. 7-Eleven Stores in Japan Getting Touch-Free Floating Holographic Self-Checkouts
Gizmodo
Andrew Liszewski
January 31, 2022


Six 7-Eleven stores in Tokyo, Japan, will soon feature floating holographic displays that will allow customers to check out without any physical contact. These displays are more hygienic than physical touchscreens and are at lesser risk of damage or wear and tear. The system replaces LCD touchscreens with Toshiba's Digi POS, which creates the illusion of a touchscreen interface floating in the air. The holographic touchscreen is not visible to anyone other than the shopper, ensuring privacy. Shoppers still must scan their items individually, and they can pay for their purchases via touchless payment cards or by scanning their mobile device.

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Researchers Use GPU Fingerprinting to Track Users Online
BleepingComputer
Bill Toulas
January 30, 2022


Scientists at French, Israeli, and Australian universities have investigated the use of graphical processing units (GPUs) to track people online with unique fingerprints. The team harnessed 2,550 devices with 1,605 distinct central processing units to demonstrate that their DrawnApart system, which uses the Web Graphics Library application programming interface (API) present on all modern Web browsers, can tally the number and speed of the GPU's execution units, measure the time needed to complete vertex renders, and perform other tasks. The process generates traces that 176 measurements extracted from 16 points can use to produce a fingerprint, and boosts the median tracking duration of a targeted user to 67% when employed with cutting-edge tracking algorithms.

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A New Method for Quantum Computing
University of Amsterdam (Netherlands)
January 28, 2022


Physicists at the University of Amsterdam in the Netherlands have proposed a new scalable quantum computing architecture using trapped ions. The technique employs a trapped-ion platform manipulated by optical tweezers and oscillating electric fields. The researchers applied a uniform electric field to an entire crystal of trapped ions, in order to control interactions between two ions selected via application of tweezer potentials. These interactions are not dependent on the distance between them, so the duration of a quantum gate's operation also is independent. This grants the architecture inherent scalability, and can confer operational performance comparable to other state-of-the-art quantum systems while presenting fewer technical hurdles.

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Better Outcomes for Newborn Cardio-Respiratory Health
Monash University (Australia)
February 1, 2022


Software developed by researchers at Australia's Monash University can provide advanced sound quality to the heart and lung monitoring of preterm and full-term infants. "The software we've created removes all of the surrounding noise from chest recordings so the heart and lung sound are separated and very clean," said Monash's Faezah Marzbanrad. "This enables doctors and nurses to listen to them very clearly without interference and better diagnose any potential issues." When used at home, the software scores the quality of the recorded chest sound, so parents know whether the doctor can analyze it, or if they must reposition the digital stethoscope and make another recording.

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New File Format Helps Researchers Reduce DNA Analysis Time
ZDNet
Aimee Chanthadavong
February 1, 2022


The SLOW5 computer file format created by researchers at Australia's University of New South Wales and Garvan Institute of Medical Research can accelerate DNA nanopore sequencing analysis, resulting in enhanced therapies for patients with cancer and other diseases. The researchers said SLOW5 can process nanopore sequencing "more than 30 times faster" than the older FAST5 file format. FAST5-formatted data routinely yields files of 1.3 terabytes following a two-week processing job for computers; SLOW5 cuts the processing time to 12 hours. Garvan's Hasindu Gamaarachchi said SLOW5 facilitates parallel computing, so several processors can perform multiple analyses simultaneously.

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Yael Hanein prepares reporter Natalie Lisbona for her lie detector test. True Story? Lie Detection Systems Go High-Tech
BBC News
Natalie Lisbona
January 31, 2022


A new method of lie detection developed by researchers at Israel's Tel Aviv University uses electrodes affixed to the face to determine whether someone is lying. The researchers said their software and algorithm, which can detect 73% of lies, have uncovered two types of liars: those who move their eyebrows involuntarily when lying, and those who are unable to conceal a slight movement where their lips meet their cheeks when lying. Converus' EyeDetect system detects lies based on involuntary eye movements, as detected by eye-tracking software. More than 65 U.S. law enforcement agencies and close to 100 agencies worldwide use EyeDetect, which claims to be 86% to 88% accurate.

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A flash signifies the creation of graphene from waste material. ML Fine-Tunes Flash Graphene
Rice University News
January 31, 2022


Researchers at Rice University and the University of Missouri are using machine learning (ML) to refine graphene synthesis from waste via flash Joule heating. The ML models adjust to variables in feedstock, and formulate ways to optimize flash procedures. Said Rice's James Tour, whose laboratory discovered the synthesis method, "Machine learning algorithms will be critical to making the flash process rapid and scalable without negatively affecting the graphene product's properties." Tour and colleagues followed the lead of materials scientists who have incorporated ML into their everyday discovery processes, in order to parse out flash Joule heating's chemical reactions. Tour said the synergy between ML and flash heating "made it possible to synthesize graphene from scrap material based entirely on the models' understanding of the Joule heating process."

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